Video-related recommendations using link structure
First Claim
1. A computer-implemented method comprising:
- receiving, at a computer system, user information associated with users of a social network and associated with media accessed by the users;
generating, by the computer system, a graph that links first representations of the users and second representations of the media based on relationships derived from the user information, wherein the first representations and the second representations comprise nodes in the graph that are linked by edges;
selecting one or more advertising labels that are descriptive of one or more advertisements;
iteratively propagating values for the one or more advertising labels among the first representations of the users and the second representations of the media using the graph that links the first representations and the second representations; and
identifying an advertisement to provide in association with a particular representation based, at least in part, on magnitudes of one or more advertising label values for the particular representation that were determined by the iterative propagation, wherein the magnitudes of the one or more advertising label values indicate how likely a user is to select one or more corresponding advertisements, wherein the particular representation comprises a representation of a particular video, and wherein the advertisement is selected for presentation in a document that includes the particular video.
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Accused Products
Abstract
The subject matter of this specification can be embodied in, among other things, a method that includes inferring labels for videos, users, advertisements, groups of users, and other entities included in a social network system. The inferred labels can be used to generate recommendations such as videos or advertisements in which a user may be interested. Inferred labels can be generated based on social or other relationships derived from, for example, profiles or activities of social network users. Inferred labels can be advantageous when explicit information about these entities is not available. For example, a particular user may not have clicked on any online advertisements, so the user is not explicitly linked to any advertisements.
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Citations
20 Claims
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1. A computer-implemented method comprising:
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receiving, at a computer system, user information associated with users of a social network and associated with media accessed by the users; generating, by the computer system, a graph that links first representations of the users and second representations of the media based on relationships derived from the user information, wherein the first representations and the second representations comprise nodes in the graph that are linked by edges; selecting one or more advertising labels that are descriptive of one or more advertisements; iteratively propagating values for the one or more advertising labels among the first representations of the users and the second representations of the media using the graph that links the first representations and the second representations; and identifying an advertisement to provide in association with a particular representation based, at least in part, on magnitudes of one or more advertising label values for the particular representation that were determined by the iterative propagation, wherein the magnitudes of the one or more advertising label values indicate how likely a user is to select one or more corresponding advertisements, wherein the particular representation comprises a representation of a particular video, and wherein the advertisement is selected for presentation in a document that includes the particular video. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A system comprising:
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a computer system; an interface of the computer system to receive social network information associated with users of a social network and media accessed by the users; a data structure generator of the computer system to generate a graph that includes representations of entities associated with the social network and that links the representations based on relationships derived from the social network information, wherein the representations comprise nodes in the graph that are linked by edges; an inferred label generator of the computer system i) to select one or more advertising labels that are descriptive of one or more advertisements, and ii) to iteratively propagate values for the one or more advertising labels among the representations of the entities associated with the social network using the graph; and an advertisement server of the computer system to identify an advertisement to provide in association with a particular representation based, at least in part, on magnitudes of one or more advertising label values for the particular representation that were determined by the iterative propagation, wherein the magnitudes of the one or more advertising label values indicate how likely a user is to select one or more corresponding advertisements, wherein the particular representation comprises a representation of a particular video, and wherein the advertisement is selected for presentation in a document that includes the particular video. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18)
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19. A computer-implemented method comprising:
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receiving, at a computer system, user information associated with users of a social network and associated with videos accessed by the users; generating, by the computer system, a graph that links graph nodes based on relationships derived from the user information, the graph nodes comprising i) user nodes representing the users, ii) ad nodes representing advertisements, and iii) video nodes representing the videos, wherein the graph includes edges that link the graph nodes together and that represent relationships among the graph nodes;
selecting one or more advertising labels to associate with the at least a portion of graph nodes, wherein the one or more advertising labels are descriptive of one or more advertisements;iteratively propagating values for the one or more advertising labels among the graph nodes using the edges; and identifying an advertisement to provide in association with a first graph node based, at least in part, on magnitudes of one or more advertising label values for the first graph node that were determined by the iterative propagation, wherein the magnitudes of the one or more advertising label values indicate how likely a user is to select one or more corresponding advertisements, wherein the first graph node comprises a video node that represents a particular video, and wherein the advertisement is selected for presentation in a document that includes the particular video. - View Dependent Claims (20)
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Specification